Description Usage Arguments Details Value Author(s)
View source: R/SYB_wrapMatrixEQTL.R
wrapMatrixEQTL
uses MatrixEQTL package for QTL analysis of expression or methylation data with SNP genotypes.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | wrapMatrixEQTL(
inputset,
SNPfile_transpAddCoded_name,
SNPfile_tfam = NULL,
covariates_file_name = NULL,
covarsampleID = "IID",
covar2adjust = NULL,
projectfolder = "QTL",
projectname = NULL,
sampleColumn = "Sample_Name",
useModel = modelLINEAR,
errorCovariance = numeric(),
QTLtype = "both",
cisDist = 1e+06,
pvOutputThreshold_cis = 1e-06,
pvOutputThreshold_tra = 1e-06,
pvOutputThreshold_all = 1e-06,
genepos = NULL,
genemart = useMart("ENSEMBL_MART_ENSEMBL", host = "feb2014.archive.ensembl.org",
dataset = "hsapiens_gene_ensembl"),
ensembl_filter = "illumina_humanht_12_v4",
updateSNPpos = FALSE,
snpmart = useMart("ENSEMBL_MART_SNP", host = "feb2014.archive.ensembl.org", dataset =
"hsapiens_snp")
)
|
inputset |
Either ExpressionSet, SummarizedExperiment, DESeqDataSet, MethylSet or data.frame containing summarized methylation Island data from COHCAP.avg.by.island-function (package COHCAP). |
SNPfile_transpAddCoded_name |
character with path to genotype file (transposed and additive coded!). |
SNPfile_tfam |
character with path to tfam file with sample information.
If NULL, sample names are expected as header line of |
covariates_file_name |
character with path to covariates file. |
covarsampleID |
Character with column name of sample IDs in covar file. |
covar2adjust |
Character vector with column names of covariates to adjust QTL analysis. Omitted if NULL. |
projectfolder |
Character containing path to output folder (will be generated if not existing). |
projectname |
Character used as suffix for output files. |
sampleColumn |
Character with column name of sample IDs in input dataset. |
useModel |
model to use (modelANOVA or modelLINEAR or modelLINEAR_CROSS). Set useModel = modelLINEAR to model the effect of the genotype as additive linear and test for its significance using t-statistic. Set useModel = modelANOVA to treat genotype as a categorical variables and use ANOVA model and test for its significance using F-test. The default number of ANOVA categories is 3. Set otherwise like this: options(MatrixEQTL.ANOVA.categories=4). Set useModel = modelLINEAR_CROSS to add a new term to the model equal to the product of genotype and the last covariate; the significance of this term is then tested using t-statistic. |
errorCovariance |
Numeric error covariance matrix. Use numeric() for homoskedastic independent errors. |
QTLtype |
Character with "both" for calculating cis and trans QTL separately, "all" for no separation of cis and trans, "cis" for cis QTLs only. |
cisDist |
Numeric maximal baisepair distance for cis gene-SNP pairs. |
pvOutputThreshold_cis |
Numeric significance threshold p-value for cis QTL tests. |
pvOutputThreshold_tra |
Numeric significance threshold p-value for trans QTL tests. |
pvOutputThreshold_all |
Numeric significance threshold p-value for all QTL tests (cis and trans mixed). |
genepos |
dataframe with 4 columns (geneid, chr, left, right) or character with path to gene position
file. If |
genemart |
biomaRt object to be used for updating gene positions. |
ensembl_filter |
Character with filter name to search in genemart. |
updateSNPpos |
Boolean. Shall SNP-positions be updated via biomaRt? |
snpmart |
biomaRt object to be used for updating SNP positions. |
Expression or methylation data can be processed for QTL analysis. Coordinates
for genes and SNPs are either given in SNPfile_transpAddCoded_name
or genepos
, respectively,
or are downloaded from biomaRt. Model type and optional covariates can be selected for analysis.
Analysis can be perfomed for either cis or trans QTLs or both simulatanously.
list containing analysis parameter and QTL results. Intermediary results and plots
are stored in projectfolder
as side effects.
Frank Ruehle
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